Microwave Radar-Based Breast Cancer Detection:Imaging in Inhomogeneous Breast Phantoms

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3D microwave tomography with huber regularization applied to realistic numerical breast phantoms

Quantitative active microwave imaging for breast cancer screening and therapy monitoring applications requires adequate reconstruction algorithms, in particular with regard to the nonlinearity and ill-posedness of the inverse problem. We employ a fully vectorial three-dimensional nonlinear inversion algorithm for reconstructing complex permittivity profiles from multi-view single-frequency scattered field data, which is based on a Gauss-Newton optimization of a regularized cost function. We tested it before with various types of regularizing functions for piecewise-constant objects from Institut Fresnel and with a quadratic smoothing function for a realistic numerical breast phantom. In the present paper we adopt a cost function that includes a Huber function in its regularization term, relying on a Markov Random Field approach. The Huber function favors spatial smoothing within homogeneous regions while preserving discontinuities between contrasted tissues. We illustrate the technique with 3D reconstructions from synthetic data at 2GHz for realistic numerical breast phantoms from the University of Wisconsin-Madison UWCEM online repository: we compare Huber regularization with a multiplicative smoothing regularization and show reconstructions for various positions of a tumor, for multiple tumors and for different tumor sizes, from a sparse and from a denser data configuration

A Comprehensive Review on Design and Development of Human Breast Phantoms for Ultra-Wide Band Breast Cancer Imaging Systems

Microwave ultra-wide band UWB imaging system is a contemporary biomedical imaging technology for early detection of breast cancers. This imaging system requires the development of breast phantoms for experimental data analysis. In order to obtain realistic results, it is very important that these phantoms mimic the characteristics of real biological breast tissue as close as possible. For this purpose, scientists and engineers make use of the dielectric properties of human breast. This paper takes a survey of mathematical formulations used to determine biological dielectric properties and then takes a review of current breast phantoms being used in UWB imaging systems with reference to the analytical dielectric measurements. At present, breast phantoms are made, both, manually in laboratory utilizing different chemicals and also by using computational electromagnetic algorithms to introduce better heterogeneity in them. They can then easily be tested by doing computer simulations. In this review paper, emphasis is made on the phantoms which are made in laboratory for doing hardware experimentations.Microwave ultra-wide band UWB imaging system is a contemporary biomedical imaging technology for early detection of breast cancers. This imaging system requires the development of breast phantoms for experimental data analysis. In order to obtain realistic results, it is very important that these phantoms mimic the characteristics of real biological breast tissue as close as possible. For this purpose, scientists and engineers make use of the dielectric properties of human breast. This paper takes a survey of mathematical formulations used to determine biological dielectric properties and then takes a review of current breast phantoms being used in UWB imaging systems with reference to the analytical dielectric measurements. At present, breast phantoms are made, both, manually in laboratory utilizing different chemicals and also by using computational electromagnetic algorithms to introduce better heterogeneity in them. They can then easily be tested by doing computer simulations. In this review paper, emphasis is made on the phantoms which are made in laboratory for doing hardware experimentations

Extracting Dielectric Properties for MRI-based Phantoms for Axillary Microwave Imaging Device

Microwave Imaging (MWI) is an emerging medical imaging technique, which has been studied to aid breast cancer diagnosis in the frequency range from 0.5 to 30 GHz. The information about the dielectric properties of each tissue is essential to assess the viability of this type of systems. However, accurate measurements of heterogeneous tissues can be very challenging, and the current available information is still very limited. In this paper, we present a methodology for extracting dielectric properties to create anatomical models of the axillary region. These models will be used in a MWI device to aid breast cancer diagnosis through the detection of metastasised axillary lymph nodes. We apply segmentation tools to Magnetic Resonance Images (MRI) of the breast and assign dielectric properties to each tissue, extracting preliminary information about the properties of axillary lymph nodes. This study may open a way to more quickly extract dielectric properties of tissues and/or validate measurements, accelerating the development of microwave-based medical devices.The authors would like to acknowledge the study with ref. CES/44/2019/ME in Hospital da Luz Lisboa (19/09/2019).info:eu-repo/semantics/publishedVersio

Near-field Sensors with Machine Learning for Breast Tumor Detection

In this work, we propose the use of an electrically small novel antenna as a probe combined with a classification algorithm for nearfield microwave breast tumor detection. The resonant probe ishighly sensitive to the changes in the electromagnetic properties of the breast tissues such that the presence of the tumor is estimatedby determining the changes in the magnitude and phase responseof the reflection coefficient of the sensor. The Principle Component placed at the middle of the probe as shown in Fig. 1. The mainAnalysis (PCA) feature extraction method is applied to emphasize the difference in the probe responses for both the healthy and thetumourous cases . We show that when a numerical realistic breast with and without tumor cells is placed in the near field of the probe, the probe is capable of distinguishing between healthy and tumorous tissue. In addition, the probe is able to identify tumors with various sizes placed in single locations

Development of 3D MRI-Based Anatomically Realistic Models of Breast Tissues and Tumours for Microwave Imaging Diagnosis

Breast cancer diagnosis using radar-based medical MicroWave Imaging (MWI) has been studied in recent years. Realistic numerical and physical models of the breast are needed for simulation and experimental testing of MWI prototypes. We aim to provide the scientific community with an online repository of multiple accurate realistic breast tissue models derived from Magnetic Resonance Imaging (MRI), including benign and malignant tumours. Such models are suitable for 3D printing, leveraging experimental MWI testing. We propose a pre-processing pipeline, which includes image registration, bias field correction, data normalisation, background subtraction, and median filtering. We segmented the fat tissue with the region growing algorithm in fat-weighted Dixon images. Skin, fibroglandular tissue, and the chest wall boundary were segmented from water-weighted Dixon images. Then, we applied a 3D region growing and Hoshen-Kopelman algorithms for tumour segmentation. The developed semi-automatic segmentation procedure is suitable to segment tissues with a varying level of heterogeneity regarding voxel intensity. Two accurate breast models with benign and malignant tumours, with dielectric properties at 3, 6, and 9 GHz frequencies have been made available to the research community. These are suitable for microwave diagnosis, i.e., imaging and classification, and can be easily adapted to other imaging modalities.info:eu-repo/semantics/publishedVersio

Modelling the head and neck region for microwave imaging of cervical lymph nodes

Tese de mestrado integrado, Engenharia Biomédica e Biofísica (Radiações em Diagnóstico e Terapia), Universidade de Lisboa, Faculdade de Ciências, 2020O termo “cancro da cabeça e pescoço” refere-se a um qualquer tipo de cancro com início nas células epiteliais das cavidades oral e nasal, seios perinasais, glândulas salivares, faringe e laringe. Estes tumores malignos apresentaram, em 2018, uma incidência mundial de cerca de 887.659 novos casos e taxa de mortalidade superior a 51%. Aproximadamente 80% dos novos casos diagnosticados nesse ano revelaram a proliferação de células cancerígenas dos tumores para outras regiões do corpo através dos vasos sanguíneos e linfáticos das redondezas. De forma a determinar o estado de desenvolvimento do cancro e as terapias a serem seguidas, é fundamental a avaliação dos primeiros gânglios linfáticos que recebem a drenagem do tumor primário – os gânglios sentinela – e que, por isso, apresentam maior probabilidade de se tornarem os primeiros alvos das células tumorais. Gânglios sentinela saudáveis implicam uma menor probabilidade de surgirem metástases, isto é, novos focos tumorais decorrentes da disseminação do cancro para outros órgãos. O procedimento standard que permite o diagnóstico dos gânglios linfáticos cervicais, gânglios que se encontram na região da cabeça e pescoço, e o estadiamento do cancro consiste na remoção cirúrgica destes gânglios e subsequente histopatologia. Para além de ser um procedimento invasivo, a excisão cirúrgica dos gânglios linfáticos representa perigos tanto para a saúde mental e física dos pacientes, como para a sua qualidade de vida. Dores, aparência física deformada (devido a cicatrizes), perda da fala ou da capacidade de deglutição são algumas das repercussões que poderão advir da remoção de gânglios linfáticos da região da cabeça e pescoço. Adicionalmente, o risco de infeção e linfedema – acumulação de linfa nos tecidos intersticiais – aumenta significativamente com a remoção de uma grande quantidade de gânglios linfáticos saudáveis. Também os encargos para os sistemas de saúde são elevados devido à necessidade de monitorização destes pacientes e subsequentes terapias e cuidados associados à morbilidade, como é o caso da drenagem linfática manual e da fisioterapia. O desenvolvimento de novas tecnologias de imagem da cabeça e pescoço requer o uso de modelos realistas que simulem o comportamento e propriedades dos tecidos biológicos. A imagem médica por micro-ondas é uma técnica promissora e não invasiva que utiliza radiação não ionizante, isto é, sinais com frequências na gama das micro-ondas cujo comportamento depende do contraste dielétrico entre os diferentes tecidos atravessados, pelo que é possível identificar regiões ou estruturas de interesse e, consequentemente, complementar o diagnóstico. No entanto, devido às suas características, este tipo de modalidade apenas poderá ser utilizado para a avaliação de regiões anatómicas pouco profundas. Estudos indicam que os gânglios linfáticos com células tumorais possuem propriedades dielétricas distintas dos gânglios linfáticos saudáveis. Por esta razão e juntamente pelo facto da sua localização pouco profunda, consideramos que os gânglios linfáticos da região da cabeça e pescoço constituem um excelente candidato para a utilização de imagem médica por radar na frequência das micro-ondas como ferramenta de diagnóstico. Até à data, não foram efetuados estudos de desenvolvimento de modelos da região da cabeça e pescoço focados em representar realisticamente os gânglios linfáticos cervicais. Por este motivo, este projeto consistiu no desenvolvimento de dois geradores de fantomas tridimensionais da região da cabeça e pescoço – um gerador de fantomas numéricos simples (gerador I) e um gerador de fantomas numéricos mais complexos e anatomicamente realistas, que foi derivado de imagens de ressonância magnética e que inclui as propriedades dielétricas realistas dos tecidos biológicos (gerador II). Ambos os geradores permitem obter fantomas com diferentes níveis de complexidade e assim acompanhar diferentes fases no processo de desenvolvimento de equipamentos médicos de imagiologia por micro-ondas. Todos os fantomas gerados, e principalmente os fantomas anatomicamente realistas, poderão ser mais tarde impressos a três dimensões. O processo de construção do gerador I compreendeu a modelação da região da cabeça e pescoço em concordância com a anatomia humana e distribuição dos principais tecidos, e a criação de uma interface para a personalização dos modelos (por exemplo, a inclusão ou remoção de alguns tecidos é dependente do propósito para o qual cada modelo é gerado). O estudo minucioso desta região levou à inclusão de tecidos ósseos, musculares e adiposos, pele e gânglios linfáticos nos modelos. Apesar destes fantomas serem bastante simples, são essenciais para o início do processo de desenvolvimento de dispositivos de imagem médica por micro-ondas dedicados ao diagnóstico dos gânglios linfáticos cervicais. O processo de construção do gerador II foi fracionado em 3 grandes etapas devido ao seu elevado grau de complexidade. A primeira etapa consistiu na criação de uma pipeline que permitiu o processamento das imagens de ressonância magnética. Esta pipeline incluiu: a normalização dos dados, a subtração do background com recurso a máscaras binárias manualmente construídas, o tratamento das imagens através do uso de filtros lineares (como por exemplo, filtros passa-baixo ideal, Gaussiano e Butterworth) e não-lineares (por exemplo, o filtro mediana), e o uso de algoritmos não supervisionados de machine learning para a segmentação dos vários tecidos biológicos presentes na região cervical, tais como o K-means, Agglomerative Hierarchical Clustering, DBSCAN e BIRCH. Visto que cada algoritmo não supervisionado de machine learning anteriormente referido requer diferentes hiperparâmetros, é necessário proceder a um estudo pormenorizado que permita a compreensão do modo de funcionamento de cada algoritmo individualmente e a sua interação / performance com o tipo de dados tratados neste projeto (isto é, dados de exames de ressonâncias magnéticas) com vista a escolher empiricamente o leque de valores de cada hiperparâmetro que deve ser considerado, e ainda as combinações que devem ser testadas. Após esta fase, segue-se a avaliação da combinação de hiperparâmetros que resulta na melhor segmentação das estruturas anatómicas. Para esta avaliação são consideradas duas metodologias que foram combinadas: a utilização de métricas que permitam avaliar a qualidade do clustering (como por exemplo, o Silhoeutte Coefficient, o índice de Davies-Bouldin e o índice de Calinski-Harabasz) e ainda a inspeção visual. A segunda etapa foi dedicada à introdução manual de algumas estruturas, como a pele e os gânglios linfáticos, que não foram segmentadas pelos algoritmos de machine learning devido à sua fina espessura e pequena dimensão, respetivamente. Finalmente, a última etapa consistiu na atribuição das propriedades dielétricas, para uma frequência pré-definida, aos tecidos biológicos através do Modelo de Cole-Cole de quatro pólos. Tal como no gerador I, foi criada uma interface que permitiu ao utilizador decidir que características pretende incluir no fantoma, tais como: os tecidos a incluir (tecido adiposo, tecido muscular, pele e / ou gânglios linfáticos), relativamente aos gânglios linfáticos o utilizador poderá ainda determinar o seu número, dimensões, localização em níveis e estado clínico (saudável ou metastizado) e finalmente, o valor de frequência para o qual pretende obter as propriedades dielétricas (permitividade relativa e condutividade) de cada tecido biológico. Este projeto resultou no desenvolvimento de um gerador de modelos realistas da região da cabeça e pescoço com foco nos gânglios linfáticos cervicais, que permite a inserção de tecidos biológicos, tais como o tecidos muscular e adiposo, pele e gânglios linfáticos e aos quais atribui as propriedades dielétricas para uma determinada frequência na gama de micro-ondas. Estes modelos computacionais resultantes do gerador II, e que poderão ser mais tarde impressos em 3D, podem vir a ter grande impacto no processo de desenvolvimento de dispositivos médicos de imagem por micro-ondas que visam diagnosticar gânglios linfáticos cervicais, e consequentemente, contribuir para um processo não invasivo de estadiamento do cancro da cabeça e pescoço.Head and neck cancer is a broad term referring to any epithelial malignancies arising in the paranasal sinuses, nasal and oral cavities, salivary glands, pharynx, and larynx. In 2018, approximately 80% of the newly diagnosed head and neck cancer cases resulted in tumour cells spreading to neighbouring lymph and blood vessels. In order to determine cancer staging and decide which follow-up exams and therapy to follow, physicians excise and assess the Lymph Nodes (LNs) closest to the primary site of the head and neck tumour – the sentinel nodes – which are the ones with highest probability of being targeted by cancer cells. The standard procedure to diagnose the Cervical Lymph Nodes (CLNs), i.e. lymph nodes within the head and neck region, and determine the cancer staging frequently involves their surgical removal and subsequent histopathology. Besides being invasive, the removal of the lymph nodes also has negative impact on patients’ quality of life, it can be health threatening, and it is costly to healthcare systems due to the patients’ needs for follow-up treatments/cares. Anatomically realistic phantoms are required to develop novel technologies tailored to image head and neck regions. Medical MicroWave Imaging (MWI) is a promising non-invasive approach which uses non-ionizing radiation to screen shallow body regions, therefore cervical lymph nodes are excellent candidates to this imaging modality. In this project, a three-dimensional (3D) numerical phantom generator (generator I) and a Magnetic Resonance Imaging (MRI)-derived anthropomorphic phantom generator (generator II) of the head and neck region were developed to create phantoms with different levels of complexity and realism, which can be later 3D printed to test medical MWI devices. The process of designing the numerical phantom generator included the modelling of the head and neck regions according to their anatomy and the distribution of their main tissues, and the creation of an interface which allowed the users to personalise the model (e.g. include or remove certain tissues, depending on the purpose of each generated model). To build the anthropomorphic phantom generator, the modelling process included the creation of a pipeline of data processing steps to be applied to MRIs of the head and neck, followed by the development of algorithms to introduce additional tissues to the models, such as skin and lymph nodes, and finally, the assignment of the dielectric properties to the biological tissues. Similarly, this generator allowed users to decide the features they wish to include in the phantoms. This project resulted in the creation of a generator of 3D anatomically realistic head and neck phantoms which allows the inclusion of biological tissues such as skin, muscle tissue, adipose tissue, and LNs, and assigns state-of-the-art dielectric properties to the tissues. These phantoms may have a great impact in the development process of MWI devices aimed at screening and diagnosing CLNs, and consequently, contribute to a non-invasive staging of the head and neck cancer

Microwave Breast Models Through T1-weighted 3-d Mri Data

Tez (Yüksek Lisans) -- İstanbul Teknik Üniversitesi, Fen Bilimleri Enstitüsü, 2013Thesis (M.Sc.) -- İstanbul Technical University, Institute of Science and Technology, 2013Son yıllarda, meme kanserinin erken teşhisi konusunda mikrodalga görüntüleme alanında yapılan çalışmalar popülerlik kazanmıştır. Bu bağlamda, insan memesinin elektromanyetik sayısal modelleri bu konuda çalışan araştırmacılara, hızlı deneysel analizler yaparak yeni teknolojilerin fizibilitesinin artırılması ve böylece daha iyi görüntüleme tekniklerinin ve aygıtlarının geliştirilmesi konularında yardımcı olmaktadır. Literatürde özel olarak sayısal mikrodalga meme modellerini konu alan bu ilk çalışmada arzu edilen türde bir model üretilebilmesi için 3 ana adım içeren bir yöntem öne sürülmüştür. Bu yöntemin alt adımları kısaca: MRI verisindeki gürültünün homomorfik filtreleme ile giderilmesi, dokuların Gauss Karışım Modeli (GMM) ile segmentasyonu ve elektromanyetik özelliklerin parçalı-doğrusal eşleme fonksiyonları ile eşlenmesi olarak tarif edilebilir. Bu çalışmada, mikrodalga meme görüntülemesi çalışmalarında kullanılmak üzere değişik şekil, ebat ve radyografik yoğunluklarda 3-boyutlu sayısal mikrodalga meme modelleri üretilmesi için etkin ve kendi kendine işleyebilen bir yöntem sunulmuştur. Memenin heterojen yapısının mekânsal bilgisi, memelerinde bir anomaliye rastlanmayan değişik hastaların yüz üstü pozisyonda alınmış T1-ağırlıklı 3-boyutlu MRI verileri kullanılarak elde edilmiştir. Dokulara ait her bir sınıf ile elektromanyetik özellikler arasında tekdüze parçalı kübik Hermitte interpolasyon yöntemi kullanılarak doğrusal olmayan bir ilişki kurulmuştur. İlgili meme dokularının elektromanyetik özellikleri Debye and Cole-Cole dağılım modelleri üzerinden tercih edilen çalışma frekansına göre belirlenmiş, böylece MRI verisindeki her bir voksel değeri uygun bağıl geçirgenlik ve iletkenlik değerleri ile eşlenmiştir. Bağıl geçirgenlik ve iletkenlik dağılımlarına dönüştürülen MRI kesitleri, doğrusal interpolasyon ile 3-boyutlu ve gerçekçi bir yapıya dönüştürülmüştür.Recent years, early detection of breast cancer in the field of electromagnetic imaging has gained high popularity. In this context, computational electromagnetic models of the human breast are used to help researchers develope better techniques and instruments for imaging, increasing the feasibility of new technologies, and doing fast experimental analysis. In this study, an effective and automated methodology for realistic numerical 3-D breast phantom development of different shapes, size and radiographic density in order to be used for different electromagnetic simulation models in microwave breast imaging research is presented. The spatial information of heterogeneity of the breast structure is collected from T1-weighted MRI slices of different patients’ in prone position with normal breast tissue (not malignant or abnormal). Each voxel in MRI data was mapped to the appropriate dielectric properties using several steps. First, bias field appears on each slice in MRI data was estimated and eliminated. After filtering of all slices, voxels belong to adipose and glandular tissues were classified into four categories. Then those tissue categories were related to electromagnetic properties of relative permittivity and conductivity by monotone piecewise polynomial cubic Hermite interpolation. Electromagnetic properties of the breast tissue are expanded to desired frequency using Debye dispersion models. Each voxel intensity value is nonlinearly mapped to the appropriate electromagnetic properties of the corresponding breast tissue. Later, the resultant slices of permittivity and conductivity are linearly interpolated to form a proper 3-D breast structure.Yüksek LisansM.Sc

Design and Simulation of Coils for High Field Magnetic Resonance Imaging and Spectroscopy

The growing availability of high-field magnetic resonance (MR) scanners has reignited interest in the in vivo investigation of metabolics in the body. In particular, multinuclear MR spectroscopy (MRS) data reveal physiological details inaccessible to typical proton (1H) scans. Carbon-13 (13C) MRS studies draw considerable appeal owing to the enhanced chemical shift range of metabolites that may be interrogated to elucidate disease metabolism and progression. To achieve the theoretical signal-to-noise (SNR) gains at high B0 fields, however, J-coupling from 1H-13C chemical bonds must be mitigated by transmitting radiofrequency (RF) proton-decoupling pulses. This irradiated RF power is substantial and intensifies with increased decoupling bandwidth as well as B0 field strength. The preferred 13C MRS experiment, applying broadband proton decoupling, thus presents considerable challenges at 7 T. Localized tissue heating is a paramount concern for all high-field studies, with strict Specific Absorption Rate (SAR) limits in place to ensure patient safety. Transmit coils must operate within these power guidelines without sacrificing image and spectral quality. Consequently, RF coils transmitting proton-decoupling pulses must be expressly designed for power efficiency as well as B1 field homogeneity. This dissertation presents innovations in high-field RF coil development that collectively improved the homogeneity, efficiency, and safety of high field 13C MRS. A review of electromagnetic (EM) theory guided a full-wave modeling study of coplanar shielding geometries to delineate design parameters for coil transmit efficiency. Next, a novel RF coil technique for achieving B1 homogeneity, dubbed forced current excitation (FCE), was examined and a coplanar-shielded FCE coil was implemented for proton decoupling of the breast at 7 T. To perform a series of simulation studies gauging SAR in the prone breast, software was developed to fuse a suite of anatomically-derived heterogeneous breast phantoms, spanning the standard four tissue density classifications, with existing whole-body voxel models. The effects of tissue density on SAR were presented and guidance for simulating the worst-case scenario was outlined. Finally, for improving capabilities of multinuclear coils during proton coil transmit, a high-power trap circuit was designed and tested, ultimately enabling isolation of 13C coil elements during broadband proton decoupling pulses. Together, this work advanced the hardware capabilities of high-field multinuclear spectroscopy with immediate applicability for performing broadband proton-decoupled 13C MRS in the breast at 7 T